Non-invasive arterial blood pressure measurement and SpO estimation using PPG signal: a deep learning framework.

Journal: BMC medical informatics and decision making
PMID: 37480040

Abstract

BACKGROUND: Monitoring blood pressure and peripheral capillary oxygen saturation plays a crucial role in healthcare management for patients with chronic diseases, especially hypertension and vascular disease. However, current blood pressure measurement methods have intrinsic limitations; for instance, arterial blood pressure is measured by inserting a catheter in the artery causing discomfort and infection.

Authors

  • Yan Chu
    McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Kaichen Tang
    Guangzhou AID Cloud Technology, No. 68 Huacheng Avenue, Tianhe District, Guangzhou, China.
  • Yu-Chun Hsu
    McWilliams School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, United States.
  • Tongtong Huang
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston.
  • Dulin Wang
    McWilliams School of Biomedical Informatics, University of Texas Health Science Center at Houston, Houston, TX, USA.
  • Wentao Li
    State Key Laboratory of Agricultural Microbiology, Huazhong Agricultural University, Wuhan 430070, Hubei, People's Republic of China.
  • Sean I Savitz
    From the Departments of Neurology (S.A.S., V.L.-R., S.L., S.I.S.), UTHealth McGovern Medical School, Houston, TX.
  • Xiaoqian Jiang
    School of Biomedical Informatics, University of Texas Health, Science Center at Houston, Houston, TX, USA.
  • Shayan Shams
    School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, Texas, USA.

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